1. A model-based image-matching technique for three-dimensional reconstruction of human motion from uncalibrated video sequences
- Author
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Tron Krosshaug and Roald Bahr
- Subjects
Matching (statistics) ,Motion analysis ,Computer science ,Movement ,Video Recording ,Biomedical Engineering ,Biophysics ,Image processing ,Kinematics ,Models, Biological ,Running ,Root mean square ,Acceleration ,Imaging, Three-Dimensional ,Motion estimation ,Methods ,Humans ,Orthopedics and Sports Medicine ,Computer vision ,business.industry ,Rehabilitation ,Biomechanical Phenomena ,Human-body model ,Joints ,Artificial intelligence ,business - Abstract
In many situations, e.g. sports injuries, three-dimensional kinematics cannot be obtained with traditional lab methods. However, if methods for reconstructing motion patterns from video sequences were available, our understanding of injury mechanisms could be improved. The aim of this study was to assess the accuracy of a new model-based image-matching technique for human motion reconstruction from one or more uncalibrated video sequences, using traditional motion analysis as a gold standard. A laboratory trial was conducted with one test subject performing jogging and side step cutting, while being filmed with three ordinary video cameras. This provided three single camera matchings, three double camera matchings and one triple camera matching for each of the motions. The test subject wore 33 reflective skin markers and was filmed with a seven-camera, 240 Hz motion analysis system. Root mean square (RMS) hip and knee flexion/extension angle differences were less than 12 degrees for all the matchings. Estimates for ad-/abduction (
- Published
- 2005